The purpose of this application is to investigate MR relaxation as a function of the spatial tissue proteomic distribution as determined by matrix assisted laser desorption/ionization imaging mass spectrometry (MALDI- IMS), a process we have termed "relaxomics". It is widely known that the relaxation phenomena that govern contrast in MR images are governed by the nature and abundance of tissue macromolecules. However, to date, a compelling method to elucidate the macromolecular correlation with tissue relaxation has not been forthcoming. The recent development of MALDI IMS provides a novel way to directly analyze tissue macromolecules in situ. When this technology is combined with mesoscopic in vivo MR imaging, one gains the ability to quantitatively correlate tissue relaxation and protein interactions. An added benefit of this development is the ability to interrogate volumetric MALDI data in light of anatomical cues and pathophysiological structures seen in the MR images. Our hypothesis is that the novel application of MALDI IMS data to in vivo imaging will lend insights into the tissue relaxation phenomena and the macromolecules that contribute therein. The aims within this application define a method to develop the tools that will enable us to achieve our long-term goal of a quantitative model of MR relaxation variations in terms of tissue proteins. To achieve this goal a framework to develop the co-registration of MALDI IMS and MR imaging is described (Aim I). Furthermore, a method to provide adequate data analysis tools for the feature-rich co- registered data is also defined (Aim II). Finally, animal studies are planned to utilize the developed tools to investigate the relaxomic properties of cancerous tissue when compared to non-cancerous tissue (Aim III). Scientifically, these studies define a novel paradigm for quantitative analysis of tissue proteomics and MR relaxation concurrently. Conversely, the methods developed in this study also allow for a novel method to interpret MALDI imaging data with complementary anatomical features found in in vivo MR imaging. Thus, this application defines a significant advancement in the study of imaging and its biophysical basis. [unreadable] [unreadable] [unreadable] [unreadable]